AI: Logistics’ extra hidden hand

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An industry inflection point

Logistics—the hidden hand that manages moving goods from source to end user—has long been seen as an industry ready to reap huge benefits from technological change. It relies on physical and digital networks to move goods safely and securely, and generates vast quantities of data, all areas ripe for the application of artificial intelligence (AI). Yet while it’s uptake may have been slower than some industries, like manufacturing and finance, those in the industry say AI is starting to have an impact on almost every element of the business, from demand generation to warehousing through to the transport, transfer, delivery and acceptance processes.

At present, the sheer scale of the industry presents a challenge that has only been partly addressed by technology. Take shipping for example. An estimated 90% of international non-bulk cargo is moved by sea, yet the majority of the shipping industry’s documentation is still recorded on paper or sent by fax. And while the broader logistics industry has embraced digitization, it is still in its early days: According to IBM researchers, only 10% of current logistics systems, data and interactions include elements of AI. This is despite a recent survey by consulting group EY that predicted the global value of goods transported would quadruple by 2050, to be worth US$68.5 trillion.

This gap leaves plenty of room for innovation and logistics is now at a significant inflection point—demand for AI is soaring as companies strive to reap the cost reductions and efficiencies it promises. A study by consulting firm McKinsey concludes that transport and logistics can derive up to $500 billion of incremental value from the use of AI over other analytical techniques, an amount second only to the travel industry.

Data-driven efficiencies

DHL, a large German logistics firm, is testing a wide range of AI applications across all its businesses, which cover air, land and sea freight. The use of machine learning and natural language processing, for example, is being applied in its Resilience360 supply chain risk management product, which processes millions of variables to assess supplier risk..
"This is really the power of using artificial intelligence to pull live information and relate it to a customer’s specific supply chain and shipments," Data Analytics Innovation Leader at DHL's Asia Pacific Innovation Center, Timothy Kooi says. "Of course it's not smart enough yet to make decisions for you, but it can give you detailed decision advice. That’s a step in the right direction."

However, to effectively train machine learning algorithms, data must be collected and stored well, which is an area that’s being addressed through advances in cloud computing and networks. "We are just starting to scratch the surface of the use cases for AI. Companies have an unfathomable amount of data at their disposal, but if this data is bad, then the output will also be bad," says Kevin McMahon, Executive Director of Mobile and Emerging Technologies at SPR, a digital technology consulting firm. "It doesn’t matter how sophisticated the AI algorithms are. Improvements in technologies like cloud computing, edge computing, networking, IoT and 5G are creating more effective ways to collect and store data, allowing AI to one day provide more accurate and actionable insights."

AI enablers

Jointown Pharmaceutical Group, a large Chinese drug distribution company, has drastically changed its operations using AI based cloud technology.

Jointown was able to refine the way it collected the vast amounts of data it generated and apply AI to that to improve its internal operations and business efficiency. By analysing the company's order history, for example, it was able to provide optimal pickup paths and reduce the number of vehicles required to fulfil the same number of orders. AI also enabled it to optimize its inventory management across its warehouse storage locations. Paperwork was digitised and the time for re-inspections was reduced to 10 seconds. From placing the order to loading the goods, the entire process now takes less than two hours.

"Jointown didn’t feel that the traditional business-driven IT model was efficient enough," Wan Yougang, Jointown Deputy Director of Operations and IT Management, says. "Instead, we prefer a strategy-driven IT model in which enterprises prioritize their future. Huawei Cloud has helped us become a driving force for business innovation, and specifically IT innovation."

Future forecasts

For all the present advances, however, it’s the future that offers the greatest promise for AI in logistics. As paperwork gets digitised, there’s hope that it will not only speed up processing but be mined for intelligence far beyond its present use. DHL’s Kooi believes AI could seek to predict the future based on the knowledge gathered from logistics data. For example, using a machine-learning based tool developed by DHL, it could predict air freight transit delays to propose proactive mitigation.

Paperwork is also an area where AI will have wide-ranging implications beyond simple efficiencies. A 2015 joint report by the World Bank and the World Trade Organisation found that countries with inefficient trade documentation requirements took more time to process imports and exports, and were more likely to have a higher poverty rate. And while many documentation requirements originate from government, some are also a result of force of habit or old systems.

DHL believes much of the human element involved in customs paper checking can be removed, detailing in a 2018 paper how an AI platform can be trained to automate customs declarations using natural language processing and the self-learning capabilities of deep learning. By using new data to continually improve its performance, findings suggest such a system could ‘ingest’ all the necessary paperwork and process it, flagging only those anomalies that require manual intervention. According to the report, Ernst and Young is already using a similar approach to detect fraudulent invoices with 97% accuracy. Wherever there are complex manual processes that require skillful knowledge of regulations, industries and customers, AI could lend a hand.

Huawei has also applied AI to its own document processing requirements. It says it used Optical Character Recognition (OCR) technology, which has a numeric value accuracy of up to 97%, to streamline both the processing and the recording of its customs documents. When combined with big data analytics, this increased the company’s customs efficiency and significantly reduced its risk exposure, according to Huawei.

The human element

For some in the supply chain, however, the holy grail of AI remains not in automating the human out of the equation but of better integrating the human into the supply chain. Gabe Batstone, CEO of contextere, an industrial software company focused on AI solutions, believes the key use of AI may be on what he calls the “last tactical mile, where warm hands touch cold steel.” This AI, he says, would enable human operators to have natural language conversations with machines, asking questions such as ‘What does this error code mean on the elevator panel?’ ‘What special tools do I need to repair this landing gear?’.

“By combining human ingenuity with AI, we are already improving the productivity and safety of the industrial workforce,” says Batstone. “Technological innovation and job creation are not mutually exclusive. In fact, the strategy to address both the opportunities and threats of a globalized, connected world should be to combine AI and humans.”

How these two visions of the future of AI and logistics resolve themselves also depends on broader decisions outside of technology. But those in the industry agree that there’s no question that AI’s success will depend on the quality of the data that it receives, and the quality of the networks over which the data travels. DHL’s Kooi points to a project it rolled out with Huawei last year to integrate narrowband communications into a truck fleet in Liuzhou, China, using Huawei’s and China Mobile’s NB-IoT chips. The chips enabled a simple improvement: coordinating trucks to arrive and unload their containers in a loading dock, at the right bay, at the right time. Being able to share and coordinate that locational information in a smart and efficient way was vital, he says. “Connectivity is absolutely key to information sharing in a timely manner,” he says.

Similarly, Contextere CEO Batstone sees AI, IoT and connectivity as vital components of the same body. “From an infrastructure perspective IoT is like the body, connectivity is the nerves and AI is the brain. To get the full potential of AI you need to be able to implement it fully at the edge with links to the cloud,” he said. “When IoT and 5G are fully realized AI will move from be being an amazing tool to begin the baseline of literally everything we do today.”

HUAWEI CONNECT 2018 – “Activate Intelligence” – will be held at the Shanghai World Expo Exhibition and Convention Center and Expo Center from October 10 to 12.

This year’s HUAWEI CONNECT conference is designed to help all businesses and organizations step over the threshold and stake their claim in the intelligent world. You will be joined by the best minds in the industry – including global ICT leaders, industry experts, and ecosystem partners – to chart the way forward and explore new opportunities.

Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home and organization for a fully connected, intelligent world. Huawei’s end-to-end portfolio of products, solutions and services are both competitive and secure. Through open collaboration with ecosystem partners, we create lasting value for our customers, working to empower people, enrich home life, and inspire innovation in organizations of all shapes and sizes. At Huawei, innovation focuses on customer needs. We invest heavily in basic research, concentrating on technological breakthroughs that drive the world forward. We have more than 180,000 employees, and we operate in more than 170 countries and regions. Founded in 1987, Huawei is a private company fully owned by its employees.

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